Sales By Country and Category
orders <- ggplot(data = Sales_Export_2019_2020, aes(x = country, y = order_value_EUR, fill = category)) + geom_smooth(aes(group = category)) + scale_y_continuous(labels = scales::comma) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplotly(orders)
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
#Total Sales of each category by country
TCCSales <- ggplot(data = CountryTotalSaleExport, aes(x = country, y = saleCategoryTotal, fill = category)) +
geom_col() + theme(axis.text.x = element_text(angle = 45, hjust = 1)) + labs(title = "Total Sales of Each Countries Exports by Category (2019-2020))", x = "Country", y = "Cost Total") + scale_y_continuous(labels = scales::comma)
ggplotly(TCCSales)
Cost Per Category for Each Country
#Total cost of each category by country
TCCCost <- ggplot(data = CountryTotalcostExport, aes(x = country, y = costCategoryTotal, colour = category)) + geom_point() + geom_line(aes(group = category)) + theme(axis.text.x = element_text(angle = 45, hjust = 1)) + labs(title = "Total Cost of Each Countries Exports by Category (2019-2020))", x = "Country", y = "Cost Total") + scale_y_continuous(labels = scales::comma)
ggplotly(TCCCost)
Gross Profit for Each Country
#Gross Profit by country
CGProfit <- ggplot(data = CountryProfit, aes(x = reorder(country, GrossProfit), y = GrossProfit)) + geom_point() + theme(axis.text.x = element_text(angle = 45, hjust = 1)) + labs(title = "Cross Profit Per Country (2019-2020))", x = "Country", y = "Total Gross Profit") + scale_y_continuous(labels = scales::comma)
ggplotly(CGProfit)